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Threat Investigator in Austin

2 active opportunities · Updated October 2026

Explore current threat investigator jobs in Austin. Filter by work mode, employment type, experience, department, date posted and distance.

MT
📍 Austin, TX, United States
✓ High-confidence listingCompany trend +1266.7%
Quick readStrong listing-quality and freshness signals

Our vision is to transform how the world uses information to enrich life for all . Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. The Logistics Security Intelligence Analyst supports Micron’s global logistics security program by producing timely, actionable intelligence on shipment risk, cargo theft trends, route exposure, carrier performance, alert activity, and logistics security incidents. This individual contributor role helps strengthen shipment visibility, support incident response, and enable data-driven decisions for valuable and sensitive shipments across Micron’s transportation network. Responsibilities: Collect, analyze, and report on logistics security data related to high-value and high-risk shipments, including shipment value, route risk, carrier performance, tracking status, alert activity, and incident history. Monitor internal, vendor, industry, open-source, and law-enforcement sources for cargo theft trends, route disruptions, regional security developments, and emerging threats. Prepare intelligence summaries, dashboards, route profiles, regional threat updates, incident trend reports, and briefing materials for logistics security leaders and multi-functional collaborators. Support lane, route, carrier, provider, and regional risk assessments by identifying risk indicators, documenting findings, and helping translate analysis into practical control recommendations. Analyze shipment monitoring alerts such as route deviation, unauthorized stop, signal loss, seal breach, geofence violation, cargo separation, and other logistics security events. Support blocking issue and incident response a

AISupply ChainLogisticsRecruitment
T
📍 Austin, Texas, United States· Full-time
✓ High-confidence listing

$100K – $500K/yr

Quick readStrong listing-quality and freshness signals

Tenstorrent is leading the industry on cutting-edge AI technology, revolutionizing performance expectations, ease of use, and cost efficiency. With AI redefining the computing paradigm, solutions must evolve to unify innovations in software models, compilers, platforms, networking, and semiconductors. Our diverse team of technologists have developed a high performance RISC-V CPU from scratch, and share a passion for AI and a deep desire to build the best AI platform possible. We value collaboration, curiosity, and a commitment to solving hard problems. We are growing our team and looking for contributors of all seniorities. We’re looking for a Staff Forward Deployed Engineer who’s excited to build with the engineers using the AI computers Tenstorrent makes. You will create continuity between customers, engineering, and AI inference service products. This is an engineering role first: you contribute production code, operate deployments, and you can explain a trade-off to customer leadership as clearly as to core engineering teams. This is a high-autonomy role with direct customer impact. This role is remote, based out of North America, with preference near one of our main hubs: Santa Clara, CA; Austin, TX; or Toronto, ON. We welcome candidates at various experience levels for this role. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting. Who You Are You understand how accelerator compute, memory, and networking topology constrain AI workloads, and don't treat hardware as a black box. You're an early adopter of AI for your work from coding to building agentic workflows that multiply your impact. You work directly with customers to understand their challenges and provide effective solutions. You are comfortable debugging across the full inference stack: from failing requests, through the serving layer, down to OOMs or kernel dispatch if n

AWSKubernetesMachine LearningAI
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